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Big Data on Kubernetes

You're reading from   Big Data on Kubernetes A practical guide to building efficient and scalable data solutions

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835462140
Length 296 pages
Edition 1st Edition
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Author (1):
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Neylson Crepalde Neylson Crepalde
Author Profile Icon Neylson Crepalde
Neylson Crepalde
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1:Docker and Kubernetes FREE CHAPTER
2. Chapter 1: Getting Started with Containers 3. Chapter 2: Kubernetes Architecture 4. Chapter 3: Getting Hands-On with Kubernetes 5. Part 2: Big Data Stack
6. Chapter 4: The Modern Data Stack 7. Chapter 5: Big Data Processing with Apache Spark 8. Chapter 6: Building Pipelines with Apache Airflow 9. Chapter 7: Apache Kafka for Real-Time Events and Data Ingestion 10. Part 3: Connecting It All Together
11. Chapter 8: Deploying the Big Data Stack on Kubernetes 12. Chapter 9: Data Consumption Layer 13. Chapter 10: Building a Big Data Pipeline on Kubernetes 14. Chapter 11: Generative AI on Kubernetes 15. Chapter 12: Where to Go from Here 16. Index 17. Other Books You May Enjoy

Services

Services provide stable endpoints to access pods running in a cluster, thus exposing our applications to users online. They allow pods to die and replicate without interrupting access to the applications running in those pods. There are several types of services in Kubernetes. We will discuss three of them in detail: ClusterIP, NodePort, and load balancer.

ClusterIP Service

A ClusterIP service provides an IP address that is only accessible inside the cluster. This IP does not change for the lifetime of the service, providing a stable endpoint to access the pods. Here is an example ClusterIP service manifest:

service_clusterip.yaml

apiVersion: v1
kind: Service
metadata:
    name: my-service
spec:
    type: ClusterIP
    selector:
    app: my-app
    ports:
    - protocol: TCP
     port: 80
     ...
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